Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendationsthat can help create accountability frameworks capable of governing these powerful technologies.

Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.

Facial recognition and affect recognition need stringent regulation to protect the public interest.

The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.

AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.

Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.

Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”

More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.

University AI programs should expand beyond computer science and engineering disciplines.AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

From DSC:This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

Chegg Math Solver is an AI-driven tool to help the student understand math. It is more than just a calculator – it explains the approach to solving the problem. So, students won’t just copy the answer but understand and can solve similar problems at the same time. Most importantly,students can dig deeper into a problem and see why it’s solved that way. Chegg Math Solver.

In every subject, there are many key concepts and terms that are crucial for students to know and understand. Often it can be hard to determine what the most important concepts and terms are for a given subject, and even once you’ve identified them you still need to understand what they mean.To help you learn and understand these terms and concepts, we’ve provided thousands of definitions, written and compiled by Chegg experts. Chegg Definition.

From DSC:I see this type of functionality as a piece of a next generation learning platform — a piece of the Living from the Living [Class] Room type of vision. Great work here by Chegg!

Likely, students will also be able to take pictures of their homework, submit it online, and have that image/problem analyzed for correctness and/or where things went wrong with it.

Credit to Jill O’Neill, who has written an engaging consideration of applications, discussions, and potentials for voice-user interfaces in the scholarly realm. She details a few use case scenarios: finding recent, authoritative biographies of Jane Austen; finding if your closest library has an item on the shelf now (and whether it’s worth the drive based on traffic).

Coming from an undergraduate-focused (and library) perspective, I can think of a few more:

asking if there are any group study rooms available at 7 pm and making a booking

finding out if [X] is open now (Archives, the Cafe, the Library, etc.)

finding three books on the Red Brigades, seeing if they are available, and saving the locations

10 predictions for tech in 2019— from enterprisersproject.com by Carla RudderIT leaders look at the road ahead and predict what’s next for containers, security, blockchain, and more

Excerpts:

We asked IT leaders and tech experts what they see on the horizon for the future of technology. We intentionally left the question open-ended, and as a result, the answers represent a broad range of what IT professionals may expect to face in the new year. Let’s dig in…

3. Security becomes must-have developer skill.Developers who have job interviews next year will see a new question added to the usual list.

5. Ethics take center stage with tech talent
Robert Reeves, CTO and co-founder, Datical: “More companies (prompted by their employees) will become increasingly concerned about the ethics of their technology. Microsoft is raising concerns of the dangers of facial recognition technology; Google employees are very concerned about their AI products being used by the Department of Defense. The economy is good for tech right now and the job market is becoming tighter. Thus, I expect those companies to take their employees’ concerns very seriously. Of course, all bets are off when (not if) we dip into a recession. But, for 2019, be prepared for more employees of tech giants to raise ethical concerns and for those concerns to be taken seriously and addressed.”’

7. Customers expect instant satisfaction“All customers will be the customer of ‘now,’ with expectations of immediate and personalized service; single-click approval for loans, sales quotes on the spot, and deliveries in hours instead of days. The window of opportunity for customer satisfaction will keep closing and technology will evolve to keep pace. Real-time analytics will become faster and smarter as data that is external to the organization, such as social, news and weather, will be included for more insights. The move to the cloud will accelerate with the growing adoption of open-source vendors.”

From DSC:Regarding #7 above…as the years progress, how do you suppose this type of environment where people expect instant satisfaction and personalized service will impact education/training?

A collective eyebrow was raised by the AI and robotics community when the robot Sophia was given Saudia citizenship in 2017 The AI sharks were already circling as Sophia’s fame spread with worldwide media attention. Were they just jealous buzz-kills or is something deeper going on? Sophia has gripped the public imagination with its interesting and fun appearances on TV and on high-profile conference platforms.

Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia’s creators may have crossed a line. What might the negative consequences be? To get answers, we need to place Sophia in the context of earlier show robots.

A dangerous path for our rights and securityFor me, the biggest problem with the hype surrounding Sophia is that we have entered a critical moment in the history of AI where informed decisions need to be made. AI is sweeping through the business world and being delegated decisions that impact significantly on peoples lives from mortgage and loan applications to job interviews, to prison sentences and bail guidance, to transport and delivery services to medicine and care.

It is vitally important that our governments and policymakers are strongly grounded in the reality of AI at this time and are not misled by hype, speculation, and fantasy. It is not clear how much the Hanson Robotics team are aware of the dangers that they are creating by appearing on international platforms with government ministers and policymakers in the audience.

We think of this as a transformation away from a mass-production model to a mass-personalization model. For us, that’s the big win in this whole process. When we move away from the large lectures in that mass-production model that we’ve used for the last 170 years and get into something that reflects each of the individual learners’ needs and can personalize their learning path through the instructional resources, we will have successfully moved the education industry to the new frontier in the learning process. We think that mass personalization has already permeated every aspect of our lives, from navigation to entertainment; and education is really the next big frontier.

From DSC:Each year the vision I outlined here gets closer and closer and closer and closer. With the advancements in Artificial Intelligence (AI), change is on the horizon…big time. Mass personalization. More choice. More control.

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms.

Is there demand for staying relevant? For learning new skills? For reinventing oneself?

From DSC:So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out.

Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney JohnsonExcerpt (emphasis DSC):
Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people.And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

From DSC:I have often reflected on differentiation or what some call personalized learning and/or customized learning.How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all.That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students

Or learners that have different physical capabilities or restrictions

Or learners that have different backgrounds and/or levels of prior knowledge

Etc., etc., etc.

Educators and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc. On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

Show me just the main points

Then add on the sub points

Then fill in the detailsOR

Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience.

To recap:

“Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.

This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)

Publishers create “overlays” or various layers that can be turned on or off by the learners

Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.

My daughter is a maker. She spends hours tinkering with sewing machines and slime recipes, building salamander habitats and the like. She hangs out with her school friends inside apps that teach math and problem solving through multi-player games. All the while, they are learning to communicate and collaborate in ways that are completely foreign to their grandparent’s generation. She is 10 years old and represents a shift in human cognitive processing brought about by the mastery of technology from a very young age. Her generation and those that come after have never known a time without technology. Personal devices have changed the shared human experience and there is no turning back.

The spaces in which this new human chooses to occupy must cater to their style of existence. They see every display as interactive and are growing up knowing that the entirety of human knowledge is available to them by simply asking Alexa. The 3D printer is a familiar concept and space travel for pleasure will be the norm when they have children of their own.

Current trends in active and collaborative learning are evolving alongside these young minds and when appropriately implemented, enable experiential learning and creative encounters that are changing the very nature of the learning process. Attention to the spaces that will support the educators is also paramount to this success. Lesson plans and teaching style must flip with the classroom. The learning space is just a room without the educator and their content.

…
8. Flexible and ReconfigurableWith floor space at a premium, classrooms need to be able to adapt to a multitude of uses and pedagogies. Flexible furniture will allow the individual instructor freedom to set up the space as needed for their intended activities without impacting the next person to use the room. Construction material choices are key to achieving an easily reconfigurable space. Raised floors and individually controllable lighting fixtures allow a room to go from lecture to group work with ease. Whiteboard paints and rail mounting systems make walls reconfigurable too!.

Active Learning, Flipped Classroom, SCALE-UP, TEAL Classroom, whatever label you choose to place before it, the classroom, learning spaces of all sorts, are changing. The occupants of these spaces demand that they are able to effectively, and comfortably, share ideas and collaborate on projects with their counterparts both in person and in the ether. A global shift is happening in the way humans share ideas. Disruptive technology, on a level not seen since the assembly line, is driving a change in the way humans interact with other humans. The future is collaborative.